Purpose – This paper applies the knowledge-based genetic algorithm to solve the optimization problem in complex products technological processes. Design/methodology/approach – The knowledge-based genetic algorithm (KGA) is defined as a hybrid genetic algorithm (GA) which combined the GA...

In recent years, omni-channel retailing has become immensely popular among both retailers and consumers. In this approach, retailers often leverage their brick-and-mortar stores to fulfill online orders, leading to the need for simultaneous decision-making on replenishment and inventory...

In this paper, we develop distribution-free models that solve the appointment sequencing and scheduling problems by assuming only moments information of job durations. We show that our min-max appointment scheduling models, which minimize the worst-case expected waiting and overtime costs out of...

Managing appointments for service systems with random job durations is a challenging task. We consider a class of appointment planning problems that involve two sets of decisions: job sequencing, i.e., determining the order in which a list of jobs should be performed by the server, and...

In this paper, we present a unified approach to study a class of cooperative games arisingfrom inventory centralization. The optimization problems corresponding to the inventory games are formulated as stochastic programs. We observe that the strong duality of stochastic linear programming not...

We consider the economic lot-sizing (ELS) game with general concave ordering cost.In this cooperative game, multiple retailers form a coalition by placing joint orders to asingle supplier in order to reduce ordering cost. When both the inventory holding costand backlogging cost are linear...